An Interpretability-Guided Framework for Responsible Synthetic Data Generation in Emotional Text
NeutralArtificial Intelligence
- The introduction of an interpretability
- This development is significant as it enables better emotion recognition, which is crucial for understanding public sentiment, while also addressing the limitations of current synthetic data approaches.
- The framework's reliance on SHAP underscores the importance of interpretability in AI, reflecting broader discussions on ethical AI practices and the need for responsible data generation methods.
— via World Pulse Now AI Editorial System




